Finding the signal processing parameter values that are most appropriate for an individual patient is one of the essential components of hearing aid fitting. In common practice, the hearing aid user only plays a small role in selecting these values. This proposal describes a data-driven method for empowering users to select their desired parameter values by adjusting two intuitive controllers (loudness and tone) that are displayed on consumer-level mobile devices that communicate wirelessly with the hearing aids. The primary innovation of this approach centers on large-scale analyses recognizing that systematic patterns in hearing loss configuration and in sound quality preference can be leveraged to reduce the dimensionality of an otherwise enormous space of potential combinations of parameter values. The resulting Dimension-Reduced Controllers (DRCs) make the most common combinations of signal processing parameter values easily accessible to the user, each controller manipulating numerous signal processing parameter values. In Phase I we will use DRCs with simulated hearing aids to explore the reliability, sound quality, and overall gain of the resulting hearing aid fits. In Phase II we will conduct a series of field trials where e examine users' abilities to adjust real hearing aids in real-world settings via mobile devices. In this Phase we will also develop market-ready mobile applications as well as communication protocols that use the wireless radios that are built into common mobile devices. We will evaluate these DRCs both as a tool to fine- tune the hearing aid parameter values after the prescription is applied and as stand-alone fitting method.